Must-Have**

- Strong proficiency in Python programming.
- Hands-on experience with PySpark and Apache Spark.
- Knowledge of Big Data technologies (Hadoop, Hive, Kafka, etc.).
- Experience with SQL and relational/non-relational databases.
- Familiarity with distributed computing and parallel processing.
- Understanding data engineering best practices.
- Experience with REST APIs, JSON/XML, and data serialization.
- Exposure to cloud computing environments.

- 5+ years of experience in Python and PySpark development.
- Experience with data warehousing and data lakes.
- Knowledge of machine learning libraries (e.g., MLlib) is a plus.
- Strong problem-solving and debugging skills.
- Excellent communication and collaboration abilities.





- Develop and maintain scalable data pipelines using Python and PySpark.
- Design and implement ETL (Extract, Transform, Load) processes.
- Optimize and troubleshoot existing PySpark applications for performance.
- Collaborate with cross-functional teams to understand data requirements.
- Write clean, effective, and well-documented code.
- Conduct code reviews and participate in design discussions.
- Ensure data integrity and quality across the data lifecycle.
- Integrate with cloud platforms like AWS, Azure, or GCP.

Implement data storage solutions and manage large-scale datasets.

📌 Developer (India)
🏢 GSB Solutions
📍 India